Search Results - (( based extraction method algorithm ) OR ( based constructive learning algorithm ))
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Machine learning in botda fibre sensor for distributed temperature measurement
Published 2023“…An alternative method is proposed, utilizing machine learning algorithms. …”
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Self learning neuro-fuzzy modeling using hybrid genetic probabilistic approach for engine air/fuel ratio prediction
Published 2017“…Machine Learning is concerned in constructing models which can learn and make predictions based on data. …”
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Defects identification on semiconductor wafer for yield improvement using machine learning / Pedram Tabatabaeemoshiri
Published 2025“…This study addresses the urgent issue of detecting hidden defects in semiconductor wafers that conventional methods overlook. This work presents a novel graph-based semi-supervised learning (GSSL) algorithm designed for wafer defect detection. …”
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A hybrid approach for personalized news recommendation with ordered clustering algorithm, rich user and news metadata
Published 2019“…Commonly, the current news recommendation systems employ the collaborative filtering-based (CF-based), Content-based filtering (Content-based) or hybrid methods. …”
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Research on the construction of an efficient and lightweight online detection method for tiny surface defects through model compression and knowledge distillation
Published 2024“…In response to the current issues of poor real-time performance, high computational costs, and excessive memory usage of object detection algorithms based on deep convolutional neural networks in embedded devices, a method for improving deep convolutional neural networks based on model compression and knowledge distillation is proposed. …”
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Classification of stock market index based on predictive fuzzy decision tree
Published 2005“…After constructing predictive FDT, Weighted Fuzzy Production Rules (WFPRs) are extracted from predictive FDT, and then more significant WFPR’s are mined by using similarity-based fuzzy reasoning method. …”
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Correlation model in the adoption of E-payment services: A machine learning approach
Published 2022“…Then, by using Correlation Based Feature selection algorithm, we select the best subset of features out of the highly correlated features to do predictive modelling. …”
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EEG-Based Person Authentication Modelling Using Incremental Fuzzy-Rough Nearest Neighbour Technique
Published 2016“…The correlation-based feature selection (CFS) method was used to select representative WPD vector subset to eliminate redundancy before combining with other features. …”
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9
Review of deep convolution neural network in image classification
Published 2017“…Then, the research status and development trend of convolution neural network model based on deep learning in image classification are reviewed, which is mainly introduced from the aspects of typical network structure construction, training method and performance. …”
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Speaker identification through feature fusion based deep learning / Rashid Jahangir
Published 2021“…In addition, DNN obtained better classification results compared with the other five machine learning algorithms that were recently utilised in speaker recognition. …”
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A vision-based deep learning approach for non-contact vibration measurement using (2+1)D CNN and optical flow
Published 2025“…A curated dataset was generated using a controlled experimental setup comprising a single object in a lab-scale environment, augmented synthetically to enhance frequency diversity. An optical flow-based preprocessing algorithm synchronized motion features in recorded video inputs with measured vibration labels, improving measurement accuracy. …”
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Artificial intelligence-driven anticancer peptide discovery
Published 2025“…Artificial intelligence (AI) has provided new methods to address these challenges, significantly improving the efficiency and accuracy of ACP screening through the application of machine learning and deep learning algorithms. …”
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Hybrid indoor positioning utilizing multipath- assisted fingerprint and geometric estimation for single base station systems
Published 2025“…The proposed method leverages room geometry and takes advantage of the multipath signal propagation to construct multiple virtual base station system model. …”
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Evaluation of intonation features on emphasized Malay words / Syazwani Nasaruddin
Published 2017“…Activities in this section are, for testing part, 314 words from 2 different speakers are evaluated by using clustering method. WEKA is a set of machine learning algorithm for data mining task. …”
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Classification with degree of importance of attributes for stock market data mining
Published 2004“…The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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Exploring a Q-learning-based chaotic naked mole rat algorithm for S-box construction and optimization
Published 2023“…This paper introduces a new variant of the metaheuristic algorithm based on the naked mole rat (NMR) algorithm, called the Q-learning naked mole rat algorithm (QL-NMR), for substitution box construction and optimization. …”
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Sound quality classification of wood used for Sarawak traditional musical instrument- Sape / Wong Tee Hao
Published 2024“…To address dataset imbalances, Synthetic Minority Oversampling Technique was used, enhancing dataset quality before training 40 machine learning classification algorithms. Among these, the Gaussian-kernel Support Vector Machine stood out, achieving remarkable performance with 88.18% validation and 93.37% test accuracies. …”
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A block-based multi-scale background extraction algorithm
Published 2010“…Approach: In this study, to extract an adaptive background, a combination of blocking and multi-scale methods is presented. …”
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An evolutionary based features construction methods for data summarization approach
Published 2015“…Here, feature construction methods are applied in order to improve the descriptive accuracy of the DARA algorithm.This research proposes novel feature construction methods, called Variable Length Feature Construction without Substitution (VLFCWOS) and Variable Length Feature Construction with Substitution(VLFCWS), in order to construct a set of relevant features in learning relational data. …”
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